This paper proposes a control strategy for managing an aggregate of commercial buildings equipped with Space Cooling Systems (SCSs), called to provide frequency control services to the main grid. The idea is to use the thermal energy stored into buildings to contribute to frequency regulation, during both normal and emergency operating conditions, always preserving the temperature comfort of end-users. Two specific algorithms are developed for two different classes of SCSs: inverter-driven SCSs, which allow the controller to define the current power demanded from the grid, and multi-state SCSs, which allow the controller to switch on-off one of the cooling units that compose the SCSs. In these two different cases, Model Predictive Control and Mixed-Integer Predictive Control, are respectively used to design a load aggregator algorithm able to coordinate the contribution to frequency regulation of each building, depending on their different thermal conditions. A test network model with a high penetration of renewable energy generation is implemented in a dedicated real-time simulation environment, in order to test the effectiveness of the proposed control techniques.

Frequency control services by a building cooling system aggregate

CONTE, FRANCESCO;
2016-01-01

Abstract

This paper proposes a control strategy for managing an aggregate of commercial buildings equipped with Space Cooling Systems (SCSs), called to provide frequency control services to the main grid. The idea is to use the thermal energy stored into buildings to contribute to frequency regulation, during both normal and emergency operating conditions, always preserving the temperature comfort of end-users. Two specific algorithms are developed for two different classes of SCSs: inverter-driven SCSs, which allow the controller to define the current power demanded from the grid, and multi-state SCSs, which allow the controller to switch on-off one of the cooling units that compose the SCSs. In these two different cases, Model Predictive Control and Mixed-Integer Predictive Control, are respectively used to design a load aggregator algorithm able to coordinate the contribution to frequency regulation of each building, depending on their different thermal conditions. A test network model with a high penetration of renewable energy generation is implemented in a dedicated real-time simulation environment, in order to test the effectiveness of the proposed control techniques.
2016
Demand response, Model Predictive Control, Frequency control
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/80849
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